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Estimating Distances from Parallaxes
by
Bailer-Jones, Coryn A. L.
in
Astronomical magnitude
/ Astronomical objects
/ Density
/ Density estimation
/ Estimation bias
/ Estimators
/ Inference
/ Parallax
/ Standard deviation
/ Stars
2015
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Estimating Distances from Parallaxes
by
Bailer-Jones, Coryn A. L.
in
Astronomical magnitude
/ Astronomical objects
/ Density
/ Density estimation
/ Estimation bias
/ Estimators
/ Inference
/ Parallax
/ Standard deviation
/ Stars
2015
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Journal Article
Estimating Distances from Parallaxes
2015
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Overview
Astrometric surveys such as Gaia and LSST will measure parallaxes for hundreds of millions of stars. Yet they will not measure a single distance. Rather, a distance must be estimated from a parallax. In this didactic article, I show that doing this is not trivial once the fractional parallax error is larger than about 20%, which will be the case for about 80% of stars in the Gaia catalog. Estimating distances is an inference problem in which the use of prior assumptions is unavoidable. I investigate the properties and performance of various priors and examine their implications. A supposed uninformative uniform prior in distance is shown to give very poor distance estimates (large bias and variance). Any prior with a sharp cut-off at some distance has similar problems. The choice of prior depends on the information one has available-and is willing to use-concerning, e.g., the survey and the Galaxy. I demonstrate that a simple prior which decreases asymptotically to zero at infinite distance has good performance, accommodates nonpositive parallaxes, and does not require a bias correction.
Publisher
University of Chicago Press
Subject
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